On the basis of existing research results,a new method for robust variable selection based on t function was proposed.The method achieves variable selection by the penalized function in the penalized estimating equation.Meanwhile,through the weight matrix and the bounded score function in the equation,the proposed method has a satisfactory resistance to outliers in independent variables and dependent variables,and can achieve the robust variable selection and estimation simultaneously.By analyzing the properties of t functions with 3 different kinds of degree of freedom,a t function with 2 degrees of freedom was used,and the method was compared with the Huber function based on robust variable selection method.The numerical simulation results show that,when data are contaminated with outliers by two kinds of contamination degree and three kinds of contamination mode,the proposed robust variable selection method based on t function performs better than that based on the Huber function,especially in variable selection.